A big shoutout to the early-stage founders who missed the application window for the Startup Battlefield 200 (SB 200) at TechCrunch Disrupt.
Extended Startup Battlefield 200 deadlineIt’s time to stop kicking this task-can down the road.
You have one extra week to apply to Startup Battlefield 200.
A shot at $100,000: TechCrunch editors will select 20 startups from the SB 200 to be Startup Battlefield finalists.
Apply to the Startup Battlefield 200 by June 17 at 11:59 p.m. PDT.
Jordan Meyer and Mathew Dryhurst founded Spawning AI to create tools that help artists exert more control over how their works are used online.
Meyer claims that, despite the fact that it’s substantially smaller than some other generative AI training data sets out there, Source.Plus’ data set is already “high-quality” enough to train a state-of-the-art image-generating model.
Generative AI models “learn” to produce their outputs (e.g., photorealistic art) by training on a vast quantity of relevant data — images, in that case.
Image Credits: Spawning“Source.Plus isn’t just a repository for training data; it’s an enrichment platform with tools to support the training pipeline,” he continued.
And, Meyer says, Spawning might build its own generative AI models using data from the Source.Plus datasets.
Human Native AI is a London-based startup building a marketplace to broker such deals between the many companies building LLM projects and those willing to license data to them.
Human Native AI also helps rights holders prepare and price their content and monitors for any copyright infringements.
Human Native AI takes a cut of each deal and charges AI companies for its transaction and monitoring services.
Human Native AI announced a £2.8 million seed round led by LocalGlobe and Mercuri, two British micro VCs, this week.
It is also a smart time for Human Native AI to launch.
What better way to spend your time than applying to this year’s Startup Battlefield 200 at TechCrunch Disrupt.
Accepting both applications and referralsWe’re accepting both quality applications and referrals for Startup Battlefield 200.
Startup Battlefield 200: Behold the perksAs they say, money isn’t everything.
A shot at $100,000: TechCrunch editors will select 20 startups from the SB 200 to be Startup Battlefield finalists.
Apply to the Startup Battlefield 200 right now.
Stability AI, the startup behind the AI-powered art generator Stable Diffusion, has released an open AI model for generating sounds and songs that it claims was trained exclusively on royalty-free recordings.
Called Stable Audio Open, the generative model takes a text description (e.g.
Stability AI says that it’s not optimized for this, and suggests that users looking for those capabilities opt for the company’s premium Stable Audio service.
Stable Audio Open also can’t be used commercially; its terms of service prohibit it.
And it doesn’t perform equally well across musical styles and cultures or with descriptions in languages other than English — biases Stability AI blames on the training data.
Meta has released the latest entry in its Llama series of open source generative AI models: Llama 3.
Meta describes the new models — Llama 3 8B, which contains 8 billion parameters, and Llama 3 70B, which contains 70 billion parameters — as a “major leap” compared to the previous-gen Llama models, Llama 2 8B and Llama 2 70B, performance-wise.
In fact, Meta says that, for their respective parameter counts, Llama 3 8B and Llama 3 70B — trained on two custom-built 24,000 GPU clusters — are are among the best-performing generative AI models available today.
So what about toxicity and bias, two other common problems with generative AI models (including Llama 2)?
The company’s also releasing a new tool, Code Shield, designed to detect code from generative AI models that might introduce security vulnerabilities.
Vana plans to let users rent out their Reddit data to train AI A startup, Vana, says it wants users to get paid for training dataIn the generative AI boom, data is the new oil.
“It does this by allowing users to aggregate their personal data in a non-custodial way … Vana allows users to own AI models and use their data across AI applications.”Here’s how Vana pitches its platform and API to developers:The Vana API connects a user’s cross-platform personal data … to allow you to personalize your application.
This month, Vana launched what it’s calling the Reddit Data DAO (Digital Autonomous Organization), a program that pools multiple users’ Reddit data (including their karma and post history) and lets them to decide together how that combined data is used.
We have crunched the numbers and r/datadao is now largest data DAO in history: Phase 1 welcomed 141,000 reddit users with 21,000 full data uploads.
“Reddit does not share non-public, personal data with commercial enterprises, and when Redditors request an export of their data from us, they receive non-public personal data back from us in accordance with applicable laws.
Meta, hell-bent on catching up to rivals in the generative AI space, is spending billions on its own AI efforts.
But an even larger chunk is being spent developing hardware, specifically chips to run and train Meta’s AI models.
Meta unveiled the newest fruit of its chip dev efforts today, conspicuously a day after Intel announced its latest AI accelerator hardware.
Google this week made its fifth-generation custom chip for training AI models, TPU v5p, generally available to Google Cloud customers, and revealed its first dedicated chip for running models, Axion.
Amazon has several custom AI chip families under its belt.
OpenAI is expanding a program, Custom Model, to help enterprise customers develop tailored generative AI models using its technology for specific use cases, domains and applications.
“Dozens” of customers have enrolled in Custom Model since.
As for custom-trained models, they’re custom models built with OpenAI — using OpenAI’s base models and tools (e.g.
Fine-tuned and custom models could also lessen the strain on OpenAI’s model serving infrastructure.
Alongside the expanded Custom Model program and custom model building, OpenAI today unveiled new model fine-tuning features for developers working with GPT-3.5, including a new dashboard for comparing model quality and performance, support for integrations with third-party platforms (starting with the AI developer platform Weights & Biases) and enhancements to tooling.
IBM has pledged to skill 2 million people in AI by 2030; Intel has said it’ll upskill over 30 million with AI in the same timeframe.
Yet it’s not clear how many AI roles will be available then.
According to a recent analysis by Lightcast, a labor market analytics firm, the demand for AI roles is decreasing, not increasing.
“Consortium members commit to developing worker pathways particularly in job sectors that will increasingly integrate artificial intelligence technology,” the spokesperson said.
Big Tech has big promises to keep, particularly where it concerns the future of work and the tech industry’s role in shaping it.
